Prognosis of adverse events in patients with suspected chronic heart failure

ABSTRACT

The present invention is in the field of clinical diagnostics. Particularly the present invention relates to the prognosis of adverse events in patients with stable chronic heart failure or being suspected of having stable chronic heart failure by determination of the level of Procalcitonin (PCT).

FIELD OF THE INVENTION

The present invention is in the field of clinical diagnostics.Particularly the present invention relates to the prognosis of adverseevents (e.g. mortality) in patients with stable chronic heart failure orbeing suspected of having stable chronic heart failure by determinationof the level of Procalcitonin (PCT).

BACKGROUND OF THE INVENTION

Procalcitonin (PCT) has become a well-established biomarker for thediagnosis of sepsis. PCT reflects the severity of a bacterial infectionand is in particular used to monitor progression of infection intosepsis, severe sepsis, or septic shock. It is possible to use PCT tomeasure the activity of the infection-associated systemic inflammatoryresponse, to control success of antibacterial therapy, and to estimateprognosis (Assicot et al. 1993. Lancet 341:515-8; Clec'h C et al. 2004.Crit Care Med 32:1166-9; Lee et al. 2004. Yonsei Med J 45:29-37; Meisneret al. 2005. Curr Opin Crit Care 11:473-480; Wunder et al. 2004. InflammRes 53: 158-163). The increase of PCT levels in patients with sepsiscorrelates with mortality (Oberhoffer et al. 1999. Clin Chem Lab Med37:363-368).

During bacterial infections, plasma PCT concentrations are typicallyabove 0.25 ng/mL. Recently, it has been found that in severalnon-infectious diseases, like coronary artery disease or acute coronarysyndromes, PCT concentrations can be elevated above the normal range butbelow the concentrations, which have been known so far to be associatedwith bacterial infections requiring antibacterial treatment, and thatthese PCT concentrations are associated with a prognosis of adverseevents in these patients (Sinnig et al. 2011. Circ J 75:1184-1191; Kellyet al. 2010. Biomarkers 15:325-331).

Patent applications EP 07015271.5 and EP 09719129.0 disclose the use ofPCT in the risk stratification of patients suffering from stablecoronary artery disease (CAD) and acute coronary syndromes (ACS),respectively.

Heart failure (HF), also termed congestive heart failure (CHF) is acardiac condition that occurs when a problem with the structure orfunction of the heart impairs its ability to supply sufficient bloodflow to meet the body's needs. It can cause a large variety of symptoms,particularly shortness of breath (SOB) at rest or during exertion and/orfatigue, signs of fluid retention such as pulmonary congestion or ankleswelling, and objective evidence of an abnormality of the structure orfunction of the heart at rest. However, some patients can be completelysymptom free and asymptomatic structural or functional abnormalities ofthe heart are considered as precursors of symptomatic heart failure andare associated with high mortality (Wang et al. 2003. Circulation 108:977-82). Heart failure is a common disease: more than 2% of the U.S.population, or almost 5 million people, are affected and 30 to 40% ofpatients die from heart failure within 1 year after receiving thediagnosis (McMurray J. J., Pfeffer M. A. 2005. Lancet 365: 1877-89).Heart failure is often undiagnosed due to a lack of a universally agreeddefinition and challenges in definitive diagnosis, particularly in theearly stage. With appropriate therapy, heart failure can be managed inthe majority of patients, but it is a potentially life threateningcondition, and progressive disease is associated with an overall annualmortality rate of 10%. It is the leading cause of hospitalization inpeople older than 65 years (Haldemann G. A. et al. 1999. Am Heart J137:352-60). As a consequence, the management of heart failure consumes1-2% of total health-care expenditure in European countries (Berry etal. 2001. Eur J Heart Fail 3: 749-53).

Chronic heart failure (chronic HF) is a long-term condition developingover months and years with a usually stable treated symptomatology. Thiscondition is associated with the heart undergoing adaptive responseswhich, however, can be deleterious in the long-term and lead to aworsening condition. Acute heart failure (AHF) is a term used todescribe exacerbated or decompensated heart failure, referring toepisodes in which a patient can be characterized as having a change inheart failure signs and symptoms resulting in a need for urgent therapyor hospitalization. AHF develops rapidly during hours or days and can beimmediately life threatening because the heart does not have time toundergo compensatory adaptations. Chronic HF may also decompensate whichmost commonly result from an intercurrent illness (such as pneumonia),myocardial infarction, arrhythmias, uncontrolled hypertension, or apatient's failure to maintain a fluid restriction, diet or medication.

Miller et al. examined in a cohort of patients with chronic HFhospitalized for decompensation of HF, the use of PCT for anintermediate-term prognosis of post-hospital cardiovascular mortality(mean follow-up 10 months) (Miller et al 2009. J Cardiovasc Trans Res2:526-535). However, procalcitonin levels were not different betweennon-survivors and survivors. In contrast, PCT levels tended to be higherin survivors than in non-survivors. Maisel et al. reported that thelevel of PCT was significantly associated with the prognosis ofshort-term (90-days) all-cause mortality in patients diagnosed withacute heart failure (Maisel et al. 2012. Eur J Heart Fail,14:278-286).

A method for the diagnosis of infections of the airways and lungs withassociated heart failure is described in EP 07817601.3.

However, it is unknown whether relatively elevated PCT concentrations inpatients with stable chronic heart failure or patients suspected ofhaving stable chronic heart failure can be associated with the prognosisof an adverse event (e.g. mortality). The possibility of predictingadverse events at presentation of the patient is important, since earlyrecognition of risk is a prerequisite for initiating measures helping toprevent the development of adverse events.

It has thus been the task of the present invention to investigatewhether PCT levels in patients with stable chronic heart failure orpatients suspected of having stable chronic heart failure are associatedwith the prognosis of adverse events (e.g. mortality).

SUMMARY OF THE INVENTION

The present invention relates to an in vitro method for the prognosis ofadverse events (e.g. mortality) in a patient with stable chronic heartfailure or being suspected of having stable chronic heart failurecomprising determining the level of procalcitonin (PCT) or fragmentsthereof in a sample from said patient and correlating the level of PCTor fragments thereof to the risk of getting an adverse event (e.g.mortality).

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1: Kaplan-Meier survival curves by quintiles of PCT for patientswith stable chronic heart failure or being suspected of having stablechronic heart failure (prediction of mortality).

FIG. 2: Kaplan-Meier survival curves for prognosis of patients with LVSDaccording to quartiles of PCT (all-cause mortality).

FIG. 3: Kaplan-Meier survival curves for prognosis of patients with LVSDaccording to quartiles of PCT (cardiovascular mortality).

FIG. 4: Kaplan-Meier survival curves for prognosis of patients with MSHDaccording to quartiles of PCT (all-cause mortality).

FIG. 5: Kaplan-Meier survival curves for prognosis of patients with MSHDaccording to quartiles of PCT (cardiovascular mortality).

FIG. 6: Kaplan-Meier survival curves for prognosis of patients withoutMSHD but with atrial fibrillation or N-terminal-proBNP (NT-proBNP)>400ng/L according to quartiles of PCT (all-cause mortality).

FIG. 7: Kaplan-Meier survival curves for prognosis of patients withoutMSHD but with atrial fibrillation or N-terminal-proBNP (NT-proBNP)>400ng/L according to quartiles of PCT (cardiovascular mortality).

FIG. 8: Kaplan-Meier survival curves for prognosis of patients in sinusrhythm and N-terminal-proBNP (NT-proBNP)<400 ng/L according to quartilesof PCT (all-cause mortality).

FIG. 9: Kaplan-Meier survival curves for prognosis of patients in sinusrhythm and N-terminal-proBNP (NT-proBNP)<400 ng/L according to quartilesof PCT (cardiovascular mortality).

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to an in vitro method for the prognosis ofadverse events (e.g. mortality) in a patient with stable chronic heartfailure or being suspected of having stable chronic heart failurecomprising determining the level of procalcitonin (PCT) or fragmentsthereof in a sample from said patient and correlating the level of PCTor fragments thereof to the risk of getting an adverse event (e.g.mortality).

In a preferred embodiment of the invention the level of PCT consistingof amino acids 1 to 116 or 2 to 116 or 3 to 116 of SEQ ID NO:1 isdetermined.

A further embodiment of the invention comprises determining the level ofone or more additional prognostic marker in a sample obtained from saidpatient, and combining both said level of procalcitonin or fragmentsthereof and said level of one or more additional prognostic marker tosaid predisposition of getting an adverse event, whereby the combinationof said level of procalcitonin or fragments thereof with said level ofone or more additional prognostic markers increases the predictive valueof said level of procalcitonin or fragments thereof for the prognosis ofadverse events.

Further markers which may be used as additional prognostic marker(s) maybe selected from the group comprising troponin, myeloperoxidase,C-reactive protein (CRP), neopterin, growth differentiation factor 15(GDF15), interleukin 1 receptor-like 1 (ST2), cystatin-C, as well as thefollowing peptides in form of their mature peptides, precursors,pro-hormones and associated prohormone fragments: atrial natriureticpeptide, adrenomedullin, endothelins, vasopressin.

In a further preferred embodiment one of said additional prognosticmarker(s) is pre-proBNP or fragments thereof (these can be proBNP orderivatives thereof, i.e. type B natriuretic peptide (BNP) orN-terminal-proBNP (NT-proBNP), as described above) in a sample obtainedfrom said patient.

In another more preferred embodiment said fragment of pre-proBNP is NTpro-BNP (SEQ ID NO:2). In another more preferred embodiment saidfragment of pre-proBNP is BNP (SEQ ID

NO:3).

In a further embodiment, the in vitro method for the prognosis ofgetting an adverse event for a patient with stable chronic heart failureor being suspected of having stable chronic heart failure furthercomprises mathematically combining said level of procalcitonin orfragments thereof with the level of one or more additional prognosticmarker, whereby the combination of said level of procalcitonin orfragments thereof with said level of additional prognostic marker(s)increases the predictive value of said level of procalcitonin orfragments thereof or the level of said related marker for getting anadverse event. The mathematical combination can be for instance analgorithm categorizing patients according to whether their level ofprocalcitonin is above or below a certain threshold value and whethertheir level of marker X (and Y, Z . . . ) is above or below a certainthreshold value.

Another subject of the invention is the use of an ultrasensitiveprocalcitonin assay having a lower limit of detection of <0.045(+/−0.010) ng/mL for determining a predisposition to an adverse event ina patient with stable chronic heart failure or being suspected of havingstable chronic heart failure.

“Prognosis” relates to the prediction of an adverse event (e.g.mortality) for a patient with stable chronic heart failure or beingsuspected of having stable chronic heart failure. This may include anestimation of the chance of recovery or the chance of death for saidpatient.

Adverse event is defined as worsening or decompensation of heartfailure, a cerebrovascular event, a cardiovascular event and mortality.

A cerebrovascular event is defined as ischemic stroke, hemorrhagicstroke or transient ischemic attack (TIA).

A cardiovascular event is defined as acute coronary syndrome includingmyocardial infarction.

Mortality is defined as cardiovascular death (attributable to e.g.myocardial ischemia and infarction, heart failure, cardiac arrest orcerebrovascular accident) and non-cardiovascular mortality (includingall other causes of death, e.g. infection, malignancies).

Heart failure (HF), also termed congestive heart failure (CHF) is acardiac condition that occurs when a problem with the structure orfunction of the heart impairs its ability to supply sufficient bloodflow to meet the body's needs. Chronic heart failure is a long-termcondition (months/years) usually with stable treated symptomatology,that is associated with the heart undergoing adaptive responses (e.g.dilation, hypertrophy) to a precipitating cause. These adaptiveresponses, however, can be deleterious in the long-term and lead to aworsening condition.

Patients with chronic HF can be grouped into stable, worsening anddecompensated chronic HF patients (see Table 1, adapted according to ESCGuidelines 2008 [Dickstein et al. 2008. Eur Heart J 29:2388-2442]).Acute heart failure (AHF) is defined as the rapid onset of symptoms andsigns secondary to abnormal cardiac function. AHF can present itself asacute de novo (new onset of acute heart failure in a patient withoutpreviously known cardiac dysfunction) or acute decompensation of chronicheart failure. Decompensation in chronic HF patients most commonlyresult from an intercurrent illness (such as pneumonia), myocardialinfarction, arrhythmias, uncontrolled hypertension, or a patient'sfailure to maintain a fluid restriction, diet or medication. Chronicheart failure, which is worsening or decompensated, as well as AHF ischaracterized as having a change in HF signs and symptoms resulting in aneed for urgent therapy or therapy adjustment and the requirement ofhospitalization (Jessup et al. 2009. Circulation 119:1977-2016). Threeclinical profiles describe these patients: 1) volume overload,manifested by pulmonary and/or systematic congestion, frequentlyprecipitated by an acute increase in chronic hypertension; 2) profounddepression of cardiac output manifested by hypotension, renalinsufficiency, and/or a shock syndrome; and 3) signs and symptoms ofboth fluid overload and shock (Jessup et al. 2009. Circulation119:1977-2016). After treatment, patients with AHF or acutedecompensated chronic HF may return to a chronic stable compensatedstate. A comparison of features for acute and chronic stable heartfailure is shown in table 2.

A patient having chronic stable heart failure or who is suspected ofhaving chronic stable heart failure is characterized by

the presence of structural or functional failure of the heart thatimpairs its ability to supply sufficient blood flow to meet the body'sneeds,

the absence of volume overload (manifested by pulmonary and/orsystematic congestion) and/or profound depression of cardiac output(manifested by hypotension, renal insufficiency and/or a shocksyndrome),

and whereas the patient is not in need of urgent therapy or therapyadjustment and does not require hospitalization.

Common factors that precipitate hospitalization for heart failure aree.g. acute myocardial ischemia, noncompliance with the medical regimen(sodium and/or fluid restriction), uncorrected high blood pressure,atrial fibrillation and other arrhythmias, pulmonary embolus orconcurrent infections (Jessup et al. 2009. Circulation 119:1977-2016).

In a preferred embodiment of the invention an adverse event occurringwithin 7 years, preferably within 5 years, more preferred within 4years, most preferred within 2 years is predicted.

In another preferred embodiment of the invention the level ofprocalcitonin or fragments thereof is correlated with one or moreclinical variables selected from a group comprising age, gender,diabetes, chronic obstructive pulmonary disease (COPD), symptoms,quality of life, New York Heart Association functional classification ofheart failure category (NYHA), Body mass index (BMI), heart rate andrhythm, systolic and diastolic blood pressure, edema and severity ofventricular dysfunction.

The term “patient” as used herein refers to a living human or non-humanorganism that is receiving medical care or that should receive medicalcare due to a disease. This includes persons with no defined illness whoare being investigated for signs of pathology. Thus the methods andassays described herein are applicable to both, human and veterinarydisease.

The term “correlating”, as used herein in reference to the use of PCT asprognostic marker, refers to comparing the presence or amount of themarker in a patient to its presence or amount in persons known to sufferfrom, or known to be at risk of, a given condition. A marker level in apatient sample can be compared to a level known to be associated with aspecific prognosis. The sample's marker level is said to have beencorrelated with a prognosis; that is, the skilled artisan can use themarker level to determine whether the patient has a specific risk tosuffer from an adverse event, and respond accordingly. Alternatively,the sample's marker level can be compared to a marker level known to beassociated with a good outcome (e.g. a low risk to suffer from anadverse event).

The term “sample” as used herein refers to a sample of bodily fluidobtained for the purpose of diagnosis, prognosis, or evaluation of asubject of interest, such as a patient. Preferred test samples includeblood, serum, plasma, cerebrospinal fluid, urine, saliva, sputum, andpleural effusions. In addition, one of skill in the art would realizethat some test samples would be more readily analyzed following afractionation or purification procedure, for example, separation ofwhole blood into serum or plasma components.

Thus, in a preferred embodiment of the invention the sample is selectedfrom the group comprising a blood sample, a serum sample, a plasmasample, a cerebrospinal fluid sample, a saliva sample and a urine sampleor an extract of any of the aforementioned samples. Preferably, thesample is a blood sample, most preferably a serum sample or a plasmasample.

According to the method, the patient with stable chronic heart failureor being suspected of having stable chronic heart failure has anincreased risk of getting an adverse event (e.g. mortality) when saiddetermined PCT level is higher than a predetermined threshold level.Preferably, the predetermined threshold level is between 0.015 and 0.05ng/mL, more preferred between 0.015 ng/mL and 0.035 ng/mL, even morepreferred between 0.015 ng/mL and 0.03 ng/mL, even more preferredbetween 0.015 ng/mL and 0.025 ng/mL, most preferred between 0.02 ng/mLand (below) 0.015 ng/mL. In a preferred embodiment the patient withstable chronic heart failure or being suspected of having stable chronicheart failure has an increased risk of getting an adverse event (e.g.mortality) when said determined PCT level is higher than 0.05 ng/mL,preferably higher than 0.035 ng/mL, more preferably higher than 0.03ng/mL, even more preferably higher than 0.025 ng/mL, even morepreferably higher than 0.02 ng/mL, most preferred higher than 0.015ng/mL.

The PCT levels of the present invention have been determined with a PCTtest format (BRAHMS KRYPTOR PCT sensitive), which has the samecalibration in the quantitative measuring range as a more sensitive PCTAssay (BRAHMS PCT LIA sensitive), the latter being able toquantitatively determine PCT levels in the normal population, givingmedian PCT levels as described in EP 09011073.5 (“Procalcitonin for theprognosis of adverse events in the asymptomatic population”). The abovementioned values might be different in other PCT assays, if these havebeen calibrated differently from BRAHMS KRYPTOR PCT sensitive. The abovementioned values shall apply for such differently calibrated PCT assaysaccordingly, taking into account the differences in calibration. Onepossibility of quantifying the difference in calibration is a methodcomparison analysis (correlation) of the PCT assay in question with theBRAHMS KRYPTOR PCT sensitive by measuring PCT in samples using bothmethods. Another possibility is to determine with the PCT assay inquestion, given this test has sufficient analytical sensitivity, themedian PCT level of a representative normal population, compare resultswith the median PCT levels as described in EP 09011073.5 (“Procalcitoninfor the prognosis of adverse events in the asymptomatic population”) andrecalculate the calibration based on the difference obtained by thiscomparison.

The sensitivity and specificity of a diagnostic and/or prognostic testdepends on more than just the analytical “quality” of the test, theyalso depend on the definition of what constitutes an abnormal result. Inpractice, Receiver Operating Characteristic curves (ROC curves), aretypically calculated by plotting the value of a variable versus itsrelative frequency in “normal” (i.e. apparently healthy) and “disease”populations (i.e. patients suffering from diabetes, insulin resistanceand/or metabolic syndrome). For any particular marker, a distribution ofmarker levels for subjects with and without a disease will likelyoverlap. Under such conditions, a test does not absolutely distinguishnormal from disease with 100% accuracy, and the area of overlapindicates where the test cannot distinguish normal from disease. Athreshold is selected, above which (or below which, depending on how amarker changes with the disease) the test is considered to be abnormaland below which the test is considered to be normal. The area under theROC curve is a measure of the probability that the perceived measurementwill allow correct identification of a condition. ROC curves can be usedeven when test results don't necessarily give an accurate number. Aslong as one can rank results, one can create a ROC curve. For example,results of a test on “disease” samples might be ranked according todegree (e.g. 1=low, 2=normal, and 3=high). This ranking can becorrelated to results in the “normal” population, and a ROC curvecreated. These methods are well known in the art (See, e.g., Hanley etal.1982. Radiology 143: 29-36). Preferably, a threshold is selected toprovide a ROC curve area of greater than about 0.5, more preferablygreater than about 0.7, still more preferably greater than about 0.8,even more preferably greater than about 0.85, and most preferablygreater than about 0.9. The term “about” in this context refers to +/−5%of a given measurement.

The horizontal axis of the ROC curve represents (1-specificity), whichincreases with the rate of false positives. The vertical axis of thecurve represents sensitivity, which increases with the rate of truepositives. Thus, for a particular cut-off selected, the value of(1-specificity) may be determined, and a corresponding sensitivity maybe obtained. The area under the ROC curve is a measure of theprobability that the measured marker level will allow correctidentification of a disease or condition (e.g. prognosis). Thus, thearea under the ROC curve can be used to determine the effectiveness ofthe test.

In certain embodiments, markers and/or marker panels are selected toexhibit at least about 70% sensitivity, more preferably at least about80% sensitivity, even more preferably at least about 85% sensitivity,still more preferably at least about 90% sensitivity, and mostpreferably at least about 95% sensitivity, combined with at least about70% specificity, more preferably at least about 80% specificity, evenmore preferably at least about 85% specificity, still more preferably atleast about 90% specificity, and most preferably at least about 95%specificity. In particularly preferred embodiments, both the sensitivityand specificity are at least about 75%, more preferably at least about80%, even more preferably at least about 85%, still more preferably atleast about 90%, and most preferably at least about 95%. The term“about” in this context refers to +/−5% of a given measurement.

Threshold levels can be obtained for instance from a Kaplan-Meieranalysis, where the occurrence of a disease or the probability of anadverse outcome and/or death is correlated with the e.g. quintiles ofthe respective markers in the population. According to this analysis,subjects with marker levels above the 80th percentile have asignificantly increased risk for getting an adverse event according tothe invention. This result is further supported by Cox regressionanalysis with adjustment for classical risk factors. The highestquartile versus all other subjects is highly significantly associatedwith increased risk for getting a disease or the probability of anadverse outcome and/or death according to the invention.

Other preferred cut-off values are for instance the 90th, 95th or 99thpercentile of a reference population. By using a higher percentile thanthe 80th percentile, one reduces the number of false positive subjectsidentified, but one might miss to identify subjects, who are atmoderate, albeit still increased risk. Thus, one might adapt the cut-offvalue depending on whether it is considered more appropriate to identifymost of the subjects at risk at the expense of also identifying “falsepositives”, or whether it is considered more appropriate to identifymainly the subjects at high risk at the expense of missing severalsubjects at moderate risk.

Other mathematical possibilities to calculate an individual's risk byusing the individual's marker level value and other prognosticlaboratory and clinical parameters are for instance the NRI (NetReclassification Index) or the IDI (Integrated Discrimination Index).The indices can be calculated according to Pencina (Pencina M J, et al.:Evaluating the added predictive ability of a new marker: from area underthe ROC curve to reclassification and beyond. Stat Med.2008;27:157-172).

The preferred detection methods comprise immunoassays in various formatssuch as for instance radioimmunoassay (RIA), chemiluminescence andfluorescence-immunoassays, Enzyme-linked immunoassays (ELISA), Luminex®based bead arrays, protein microarray assays, and rapid test formatssuch as for instance immunochromatographic strip tests.

The assays can be homogenous or heterogeneous assays, competitive andnon-competitive assays. In a particularly preferred embodiment, theassay is in the form of a sandwich assay, which is a non-competitiveimmunoassay, wherein the molecule to be detected and/or quantified isbound to a first antibody and to a second antibody. The first antibodymay be bound to a solid phase, e.g. a bead, a surface of a well or othercontainer, a chip or a strip, and the second antibody is an antibodywhich is labeled, e.g. with a dye, with a radioisotope, or a reactive orcatalytically active moiety. The amount of labeled antibody bound to theanalyte is then measured by an appropriate method. The generalcomposition and procedures involved with “sandwich assays” arewell-established and known to the skilled person (The ImmunoassayHandbook, Ed. David Wild, Elsevier LTD, Oxford; 3rd ed. (May 2005),ISBN-13: 978-0080445267; Hultschig C et al., Curr Opin Chem Biol. 2006Feb;10(1):4-10. PMID: 16376134, incorporated herein by reference).

In a particularly preferred embodiment the assay comprises two capturemolecules, preferably antibodies which are both present as dispersionsin a liquid reaction mixture, wherein a first labelling component isattached to the first capture molecule, wherein said first labellingcomponent is part of a labelling system based on fluorescence- orchemiluminescence-quenching or amplification, and a second labellingcomponent of said marking system is attached to the second capturemolecule, so that upon binding of both capture molecules to the analytea measurable signal is generated that allows for the detection of theformed sandwich complexes in the solution comprising the sample.

Even more preferred, said labeling system comprises rare earth cryptatesor rare earth chelates in combination with fluorescence dye orchemiluminescence dye, in particular a dye of the cyanine type.

In the context of the present invention, fluorescence based assayscomprise the use of dyes, which may for instance be selected from thegroup comprising FAM (5-or 6-carboxyfluorescein), VIC, NED, Fluorescein,Fluoresceinisothiocyanate (FITC), IRD-700/800, Cyanine dyes, such asCY3, CYS, CY3.5, CY5.5, Cy7, Xanthen,6-Carboxy-2′,4′,7′,4,7-hexachlorofluorescein (HEX), TET,6-Carboxy-4′,5′-dichloro-2′,7′-dimethodyfluorescein (JOE),N,N,N′,N′-Tetramethyl-6-carboxyrhodamine (TAMRA), 6-Carboxy-X-rhodamine(ROX), 5-Carboxyrhodamine-6G (R6G5), 6-carboxyrhodamine-6G (RG6),RHODAMINE, RHODAMINE GREEN, RHODAMINE RED, RHODAMINE 110, BODIPY dyes,such as BODIPY TMR, Oregon Green, Coumarines such as Umbelliferone,Benzimides, such as Hoechst 33258; Phenanthridines, such as TEXAS RED,YAKIMA YELLOW, ALEXA FLUOR, PET, Ethidiumbromide, Acridinium dyes,Carbazol dyes, Phenoxazine dyes, Porphyrine dyes, Polymethin dyes, andthe like.

In the context of the present invention, chemiluminescence based assayscomprise the use of dyes, based on the physical principles described forchemiluminescent materials in Kirk-Othmer, Encyclopedia of chemicaltechnology, 4^(th) ed., executive editor, J. I. Kroschwitz; editor, M.Howe-Grant, John Wiley & Sons, 1993, vol.15, p. 518-562, incorporatedherein by reference, including citations on pages 551-562. Preferredchemiluminescent dyes are acridiniumesters.

As mentioned herein, an “assay” or “diagnostic assay” can be of any typeapplied in the field of diagnostics. Such an assay may be based on thebinding of an analyte to be detected to one or more capture probes witha certain affinity. Concerning the interaction between capture moleculesand target molecules or molecules of interest, the affinity constant ispreferably greater than 10⁸ M⁻¹.

In the context of the present invention, “capture molecules” aremolecules which may be used to bind target molecules or molecules ofinterest, i.e. analytes (i.e. in the context of the present inventionPCT and fragments thereof), from a sample. Capture molecules must thusbe shaped adequately, both spatially and in terms of surface features,such as surface charge, hydrophobicity, hydrophilicity, presence orabsence of lewis donors and/or acceptors, to specifically bind thetarget molecules or molecules of interest. Hereby, the binding may forinstance be mediated by ionic, van-der-Waals, pi-pi, sigma-pi,hydrophobic or hydrogen bond interactions or a combination of two ormore of the aforementioned interactions between the capture moleculesand the target molecules or molecules of interest. In the context of thepresent invention, capture molecules may for instance be selected fromthe group comprising a nucleic acid molecule, a carbohydrate molecule, apeptide nucleic acid (PNA) molecule, a protein, an antibody, a peptideor a glycoprotein. Preferably, the capture molecules are antibodies,including fragments thereof with sufficient affinity to a target ormolecule of interest, and including recombinant antibodies orrecombinant antibody fragments, as well as chemically and/orbiochemically modified derivatives of said antibodies or fragmentsderived from the variant chain with a length of at least 12 amino acidsthereof.

In a preferred embodiment of the invention procalcitonin or fragmentsthereof of at least 12 amino acids in length is used for antibioticguidance in patients with stable chronic heart failure or patients beingsuspected of having stable chronic heart failure having an increasedrisk of getting an adverse event.

It is even more preferred that an antibiotic is administered when thelevel of procalcitonin or fragments thereof of at least 12 amino acidsin length in a sample of a bodily fluid of a patient with stable chronicheart failure or a patient being suspected of having stable chronicheart failure is between 0.015 and 0.05 ng/ml, more preferred between0.015 ng/mL and 0.035 ng/mL, even more preferred between 0.015 ng/mL and0.03 ng/mL, even more preferred between 0.015 ng/mL and 0.025 ng/mL,most preferred between 0.02 ng/mL and (below) 0.015 ng/mL.

It is even more preferred that an antibiotic is administered when thelevel of procalcitonin or fragments thereof of at least 12 amino acidsin length in a sample of a bodily fluid of a patient with stable chronicheart failure or a patient being suspected of having stable chronicheart failure is higher than 0.05 ng/mL, preferably higher than 0.035ng/mL, more preferably higher than 0.03 ng/mL, even more preferablyhigher than 0.025 ng/mL, even more preferably higher than 0.02 ng/mL,most preferred higher than 0.015 ng/mL.

EXAMPLES Example 1 Study Population and Procedures

Patients enrolled were consecutive referrals to a community-based CHFprogram in Kingston-upon-Hull and the East Riding of Yorkshire, UK,serving a population of 600 000 people between August 2001 and June2009. Patients with suspected stable chronic heart failure were referredfrom the local community to a specialist clinic for the diagnosis andmanagement of possible stable chronic heart failure and were invited toparticipate. Consenting patients underwent a systematic evaluationincluding prior medical history, medications, symptoms, signs, electro-and echocardiograms, standard hematology and biochemistry profiles andmeasurement of PCT and amino-terminal pro-brain natriuretic peptide(NT-proBNP).

Results

Of 1891 patients enrolled, the median age was 72 years (interquartilerange [IQR]: 64 to 78), 669 were women, 807 had left ventricularsystolic dysfunction (LVSD), 400 had no major echocardiographicabnormalities other than LVSD, 192 had no major echo abnormality but anNT-proBNP >400 ng/L (of whom 65 had atrial fibrillation and 15 had eGFR<30 ml/min) and 492 had none of the above. Median (IQR) PCT overall was0.022 (0.017-0.047) ng/mL and for each of the four sub-groups was 0.023(0.018-0.032), 0.022 (0.017-0.031), 0.024 (0.019-0.035) and 0.020(0.016-0.025) ng/mL respectively. Over a median follow-up of 5.0 (IQR:3.4-7.1) years, 783 (41.8%) patients died, 447 of cardiovascular causes.In univariable analysis, log (PCT) was strongly related to all-cause,cardiovascular and non-cardiovascular mortality (Hazard Ratio [HR]: 1.91with 95% CI: (1.73-2.11), HR: 1.94 (1.71-2.21) and HR: 1.89(1.61-2.22)respectively, p<0.001 for all). The HR for all-cause mortality by PCTquintiles for univariate Cox-regression analysis (unadjusted andadjusted for age and gender) are shown in Table 3. In a multi-variableCox-regression model, PCT provided additional prognostic information to17 standard clinical variables (age, sex, etiology, diabetes, COPD,symptoms, quality of life, NYHA, BMI, heart rate and rhythm, systolicblood pressure, edema, severity of ventricular dysfunction, hemoglobinand creatinine and NT-proBNP) for all-cause mortality.

Example 2 Study Population and Procedures

Further to the patients enrolled in Example 1, 651 additional patientswith suspected stable chronic heart failure were included into thestudy. Again, these patients who signed a consent to participate in thestudy, underwent a systematic evaluation including prior medicalhistory, medications, symptoms, signs, electro- and echocardiograms,standard hematology and biochemistry profiles and measurement of PCT andamino-terminal pro-brain natriuretic peptide (NT-proBNP).

Results

Of 2542 patients enrolled in total, 1100 had left ventricular systolicdysfunction (LVSD). Out of 1442 patients with no LVSD n=415 patients hadmajor structural heart disease (MSHD). Patient characteristics weredescribed by quartiles of plasma PCT (Table 4) and by top and bottomdecile to show impact of extreme values. Variables are shown aspercentages or median and inter-quartile range. Simple and multiplelinear regression models were used to identify independent variablesassociated with an inverse transformation of PCT (Table 5). Predictorsof all-cause mortality (with and without PCT included) are shown inTable 6. Patients with events, Hazard Ratio for the highest versuslowest quartile of PCT and C-statistics are summarized in Table 7.Kaplan-Meier curves were used to compare survival probabilities ofspecified outcomes (all-cause mortality, cardiovascular mortality) byphenotypes (patients with LVSD, MSHD, without MSHD but with atrialfibrillation or NT-proBNP>400 ng/L, and patients in sinus rhythm andNT-proBNP<400ng/L, respectively) (FIGS. 2 to 9).

Again PCT was strongly related to all-cause and cardiovascular mortality(unadjusted Hazard Ratio [HR]: 3.46 with 95% CI: (2.63-4.56) and HR:3.72 (2.58-5.35) respectively, p<0.001 for both). On multivariableanalysis, higher plasma PCT concentrations are associated with worserenal function, greater age, ischaemic heart disease and with markers ofmore severe heart failure but not other markers of infection orinflammation such as High Sensitivity C-Reactive Protein (hsCRP) orwhite cell count. Amongst patients with LVSD, PCT predicts all-cause andcardiovascular mortality, especially heart failure deaths, independentlyof other prognostic markers including NT-proBNP. PCT also predictsmortality in patients without LVSD, including patients in whom thediagnosis of heart failure has been refuted but this appears to bemainly non-cardiovascular.

TABLE 1 Classification of Heart failure (according to the ESCGuidelines, 2008) Classification Definition New onset (firstpresentation) Acute or slow onset Transient Recurrent or episodicChronic (persistent) Stable, worsening or decompensated

TABLE 2 Comparison of acute and chronic heart failure Acute HF AcuteStable Feature New onset HF decompensated HF chronic HF Symptom severityMarked Marked Mild to moderate Pulmonary edema Frequent Frequent RarePeripheral edema Rare Frequent Frequent Weight gain Non to mild MarkedFrequent Total body volume No or mild Markedly increased Increasedincrease Cardiac Uncommon Common Common hypertrophy Wall stress ElevatedMarkedly elevated Elevated Acute ischemia Common Occasional RareHypertensive crisis Common Occasional Rare

TABLE 3 HR for all-cause mortality by PCT quintiles for univariateCox-regression analysis PCT in ng/mL HR HR (adjusted by (Quintile)(unadjusted) age and gender)  0.018-0.020 (2^(nd)) 1.7891.673 >0.020-0.025 (3^(rd)) 2.018 1.661 >0.025-0.035 (4^(th)) 2.8262.359     >0.035 (5^(th)) 3.905 2.995

TABLE 4 Patient characteristics according to quantiles of PCT LowestLowest Quartile Quartile Highest Highest Decile Quartile 2 3 QuartileDecile N 254 635 636 636 635 254 PCT (pg/ml) 13 (12-14) 15 (13-16) 19(18-21) 25 (23-28) 43 (35-62) 69 (54-94) Age (years) 66 (58-74) 69(60-7) 71 (63-77) 73 (66-79) 75 (68-80) 75 (68-81) Men (%) 143 (56%) 372(59%) 402 (63%) 423 (67%) 420 (66%) 160 (63%) IHD (%) 124 (49%) 324(51%) 323 (51%) 332 (53%) 328 (52%) 112 (45%) DM (%) 32 (14%) 98 (17%)110 (18%) 104 (18%) 154 (27%) 66 (29%) COPD (%) 19 (8%) 55 (9%) 62 (10%)76 (12%) 67 (11%) 32 (13%) NYHA (III/IV) (%) 43 (17%) 105 (17%) 146(23%) 159 (25%) 210 (33%) 86 (34%) SOB ADL 29 (11%) 67 (11%) 95 (15%)115 (18%) 138 (22%) 61 (24%) Severe (%) edema > mild (%) 6 (2%) 24 (4%)18 (3%) 28 (4%) 47 (7%) 24 (9%) Poor Overall 45 (18%) 110 (17%) 129(20%) 147 (23%) 188 (30%) 87 (34%) Health Loop diuretic (%) 114 (46%)312 (50%) 367 (59%) 414 (67%) 497 (80%) 204 (81%) BMI (kg/m²) 27.4(24.0-31.3) 27.8 (24.5-31.4) 28.2 (24.9-31.6) 27.9 (25.0-31.9) 28.3(25.1-32.2) 28.2 (25.1-32.4) HR (bpm) 67 (60-76) 67 (59-77) 69 (59-80)70 (60-84) 75 (63-88) 78 (64-90) SBP (mmHg) 137 (120-156) 139 (122-156)140 (124-158) 138 (120-154) 133 (116-155) 132 (113-154) Sinus Rhythm (%)195 (77%) 487 (77%) 470 (74%) 454 (71%) 403 (64%) 161 (63%) QRS (msec)96 (86-110) 98 (86-116) 100 (88-124) 102 (88-122) 102 (90-130) 102(88-126) LA diam/BSA 2.0 (1.8-2.3) 2.0 (1.8-2.3) 2.1 (1.8-2.4) 2.1(1.8-2.4) 2.2 (1.9-2.5) 2.2 (2.0-2.6) (cm/m²) LVEDD/BSA 2.7 (2.4-3.1)2.8 (2.4-3.2) 2.9 (2.5-3.3) 2.9 (2.5-3.3) 2.9 (2.5-3.3) 3.0 (2.6-3.4)(cm/m²) MR > mild (%) 55 (22%) 129 (20%) 146 (23%) 128 (20%) 201 (32%)86 (34%) Hb (g/dL) 13.7 (12.7-14.5) 13.7 (12.8-14.6) 13.5 (12.5-14.6)13.5 (12.4-14.7) 12.9 (11.0-14.1) 12.5 (11.2-13.9) WBCC (×10⁹/L) 6.8(5.7-7.9) 6.6 (5.6-7.9) 6.8 (5.8-8.1) 7.1 (5.8-8.4) 7.4 (6.0-8.8) 7.6(6.1-8.9) hsCRP (mg/L) 2.1 (0.8-4.7) 2.5 (1.0-4.8) 3.1 (1.6-6.0) 4.5(2.1-8.0) 6.9 (3.4-15.0) 9.3 (4.2-29.0) Sodium 139 (137-140) 139(137-141) 139 (137-141) 139 (138-141) 139 (136-141) 138 (136-141)(mmol/L) Urea 5.1 (4.0-6.3) 5.4 (4.4-6.5) 5.9 (4.8-7.4) 6.9 (5.4-8.9)8.9 (6.2-14.0) 10.1 (6.8-16.0) (mmol/L) Creatinine 83 (72-98) 87(75-101) 94 (81-111) 104 (88-127) 127 (99-171) 136 (102-195) (μmol/L)eGFR 76 (65-88) 73 (61-85) 66 (56-80) 60 (47-72) 48 (33-62) 41 (28-58)(ml/min/1.73 m²) Cholesterol 4.5 (3.9-5.4) 4.6 (3.8-5.5) 4.6 (4.0-5.6)4.6 (3.9-5.6) 4.6 (3.8-5.5) 4.4 (3.8-5.5) (mmol/L) ALT (iu/L) 20 (17-26)20 (17-26) 21 (17-27) 21 (17-28) 21 (17-29) 22 (16-33) Alk Phos (iu/L)68 (58-84) 69 (57-85) 71 (59-87) 72 (59-88) 76 (63-99) 83 (65-107)Albumin (g/L) 38 (27-40) 38 (37-40) 38 (36-40) 38 (36-40) 36 (34-39) 36(32-39) NT-proBNP (ng/L) 438 (144-1166) 456 (136-1198) 627 (173-1593)766 (196-2056) 1,662 (505-4262) 2,017 (632-5734)

TABLE 5 Predictors of plasma PCT (inverse transformation) onmulti-variable analysis Correlation Coefficient 95% CI SE t p (R²) Log−22.039 (−24.21 −19.86) 1.107 −19.89 <0.001 −0.46 (p < 0.001)(creatinine) Heart Rate −0.139 (−0.179 −0.099) 0.020 −6.82 <0.001 −0.16(p < 0.001) (bpm) Age (years) −0.193 (−0.264 −0.122) 0.036 −5.34 <0.001−0.24 (p < 0.001) Edema 5.11 0.006 −0.16 (p < 0.001) severity Mild−2.435 (−4.03 −0.834) 0.816 −2.98 0.003 Severe −2.784 (−5.94 0.376) 1.61−1.73 0.084 Body Mass −0.1856 (−0.308, −0.062) 0.062 −2.95 0.003 −0.03(p = 0.087) Index Ischaemic 2.020 (0.625, 3.414) 0.711 2.84 0.005 −0.01(p = 0.659) Heart Disease Log (NT- −0.780 (−1.375, −0.186) 0.303 −2.570.010 −0.28 (p < 0.001) proBNP)

TABLE 6 Predictors of All-Cause Mortality (with and withoutProcalcitonin excluded) With Procalcitonin Without ProcalcitoninVariable t HR t HR Age (per decade) 11.79 1.77 (1.61-1.95) 11.56 1.76(1.60-1.94) Log(NT-proBNP) 9.65 1.34 (1.27-1.43) 10.08 1.36 (1.28-1.45)Log (PCT) 5.38 1.33 (1.19-1.47) — — COPD 4.69 1.54 (1.28-1.84) 4.87 1.56(1.31-1.87) NYHA (I-II/III-IV) 4.14 1.36 (1.17-1.57) 4.15 1.36(1.17-1.57) Diabetes Mellitus 3.54 1.32 (1.13-1.55) 3.26 1.29(1.11-1.51) Women −2.71 0.82 (0.71-0.95) −2.40 0.84 (0.73-0.97)Hemoglobin(g/dL) −2.33 0.95 (0.91-0.99) −2.47 0.95 (0.91-0.99)Breathlessness on 3.10 2.77 ADL Some 0.24 1.02 (0.86-1.22) 0.38 1.04(0.87-1.23) A lot 2.09 1.23 (1.01-1.49) 2.06 1.23 (1.05-1.59)Self-Rating of 2.53 2.91 Overall health Average 1.28 1.11 (0.95-1.31)1.33 1.12 (0.96-1.32) Poor 2.27 1.27 (1.03-1.56) 2.43 1.29 (1.06-1.59)Log(creatinine) 1.98 1.23 (1.00-1.52) 4.50 1.55 (1.28-1.29)

TABLE 7 Patients with events, Hazard Ratio for the highest v. lowestQuartile of Procalcitonin and C-Statistic Other MSHD or Not SR or NoMSHD/ NT-proBNP > SR/NT-proBNP < Overall LVSD 400 ng/L 400 ng/L N= 2,5421,100 793 649 Numbers of Patients with an Event within next 3 yearsAll-Cause 549 306 202 41 Mortality Cardiovascular 338 214 110 14Mortality Heart Failure 82 57 25 0 Death Non-CV Death 200 87 89 24Cancer Death 63 34 17 12 Hazard Ratios - Unadjusted and Adjusted for Sexand Variables in Table 4 All-Cause 3.46 (2.63-4.56) 3.41 (2.32-5.01)3.09 (1.97-4.85) 2.56 (1.09-6.03) Mortality 1.97 (1.47-2.65) 2.18(1.44-3.29) 1.69 (1.04-2.77) 1.98 (0.74-5.26) Cardiovascular 3.72(2.58-5.35) 3.69 (2.28-5.96) 3.60 (1.66-5.64) 1.22 (0.20-7.52) Mortality1.91 (1.29-2.82) 2.28 (1.37-3.81) 1.49 (0.76-2.92) 0.57 (0.07-4.96)Heart Failure  7.05 (2.76-17.98) 22.36 (3.02-165.53 2.24 (0.72-6.96) —Death 2.39 (0.89-6.41)  9.43 (1.24-71.90) 1.25 (0.34-4.62) Non-CV Death3.15 (2.05-4.83) 2.67 (1.38-5.15) 3.53 (1.77-7.05) 1.84 (0.95-3.96) 2.06(1.29-3.27) 1.84 (0.90-3.75) 2.27 (1.08-4.75) 2.77 (0.85-8.97)C-Statistic All-Cause 0.695 0.668 0.680 0.709 Mortality Cardiovascular0.688 0.666 0.684 0.638 Mortality Heart Failure 0.740 0.730 0.777 —Death Non-CV Death 0.713 0.678 0.699 0.708

Sequences SEQ ID NO: 1 (amino acid sequence of PCT): 1APFRSALESS PADPATLSED EARLLLAALV QDYVQMKASE LEQEQEREGS 51SLDSPRSKRC GNLSTCMLGT YTQDFNKFHT FPQTAIGVGA PGKKRDMSSD 101LERDHRPHVS MPQNAN SEQ ID NO: 2 (amino acid sequence of NT-pro-BNP): 1HPLGSPGSAS DLETSGLQEQ RNHLQGKLSE LQVEQTSLEP LQESPRPTGV 51WKSREVATEG IRGHRKMVLY TLRAPR SEQ ID NO: 3 (amino acid sequence of BNP):1 SPKMVQGSGC FGRKMDRISS SSGLGCKVLR RH

1. A method of predicting the risk of getting an adverse event for apatient with stable chronic heart failure or being suspected of havingstable chronic heart failure the method comprising: determining thelevel of procalcitonin or fragments thereof of at least 12 amino acidsin length in a sample of bodily fluid of said patient, correlating saidlevel of procalcitonin or fragments thereof with the risk of getting anadverse event for said patient. 2-12. (canceled)
 13. Use of PCT forantibiotic guidance in patients with stable chronic heart failure orpatients being suspected of having stable chronic heart failure havingan increased risk of getting an adverse event the method comprising:determining the level of procalcitonin or fragments thereof of at least12 amino acids in length in a sample of bodily fluid of said patientcorrelating said level of procalcitonin or fragments thereof with therisk of getting an adverse event for said patient.
 14. (canceled)
 15. Amethod for determining an enhanced risk of a patient with stable chronicheart failure or suspected of having stable chronic heart failuresuffering an adverse event, comprising: (a) detecting and quantitatingthe level of procalcitonin (PCT), or a fragment thereof consisting ofamino acids 1 to 116 or 2 to 116 or 3 to 116 of SEQ ID NO:1, in a sampleof bodily fluid of said patient, wherein the detection and quantitationcomprises a PCT detection assay wherein the sample is contacted with anantibody that specifically binds to PCT to form a detectablePCT:antibody complex, and detecting and quantitating the complex; and(b) comparing said level of PCT or fragments thereof to a statisticallysignificant predetermined threshold level, wherein, when said level ofprocalcitonin or fragments thereof exceeds said threshold level, saidpatient is determined to have an enhanced risk of suffering an adverseevent.